# Randomized controlled trial of a novel digital health solution to enable remote fetal monitoring in high risk pregnancies

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2022 · $1,021,360

## Abstract

Project Summary
Women carrying high risk pregnancies require frequent, in-person fetal monitoring appointments to reduce
their risk of stillbirth. However, public health emergencies, such as the COVID-19 pandemic, lead to reduced
access to care access and elevated risk of infectious exposures, that disparately impact these women. These
secondary effects are even more challenging for underserved and disadvantaged women, for whom the
economic and logistic barriers to multiple visits can prove insurmountable. For example, Black women face
increased risk of stillbirth as well as of COVID-19 complications, while simultaneously facing more significant
barriers to care such as transportation costs, childcare and employment inflexibility. Telehealth solutions have
been shown to improve access to prenatal care while reducing racial disparities. Unfortunately, no digital
solution has been successfully implemented to enable remote fetal monitoring for high risk pregnancies.
Over the past 3 years, we have conducted validation trials of a novel, device and digital platform, called Invu,
which uses bio-potential and acoustic sensors to passively detect maternal and fetal heart rate via a wearable,
self-administered belt. This platform was just recently approved by the FDA for detecting fetal heart rate as part
of a virtual prenatal care visit. However, we recently validated a novel algorithm for detecting uterine
contractions using Invu, using the amplitude modulation of maternal signals. The addition of uterine activity
monitoring provides Invu with all of the components to remotely conduct a non-stress test (NST), one of the
most common fetal surveillance tests used to reduce the risk of stillbirth. However, prior devices have failed to
achieve widespread uptake. Thus, it is critical to deploy a deliberate, strategic and multi-faceted approach to
implementing a remote NST monitoring solution to maximize its widespread dissemination.
We have gathered a multi-disciplinary team of investigators experienced in behavioral and communal
interventions, health disparities, innovation methodologies, maternal fetal medicine, clinical trial design and
implementation science. We will gather robust stakeholder feedback from patients, providers and clinical team
members and utilize the valuable perspective to inform a workflow optimization process using rapid-cycle
innovation techniques. This will allow us to preemptively identify and address potential barriers to
implementation. We will then conduct a rigorous hybrid, randomized controlled trial that will first focus on
demonstrating the effectiveness of a remote NST program to improve patient adherence, with specific attention
to ensure that barriers faced by Black women are being addressed. At the same time, we will use a mixed
methods strategy, via validated surveys and structured interviews, to study the key factors to widespread
implementation and deployment. With 1 million high risk pregnancies delivering annually i...

## Key facts

- **NIH application ID:** 10490447
- **Project number:** 5R01HD105446-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Nadav Schwartz
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,021,360
- **Award type:** 5
- **Project period:** 2021-09-20 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10490447

## Citation

> US National Institutes of Health, RePORTER application 10490447, Randomized controlled trial of a novel digital health solution to enable remote fetal monitoring in high risk pregnancies (5R01HD105446-02). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10490447. Licensed CC0.

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